Focused On-demand Library for Potassium channel subfamily K member 9

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We employ our advanced, specialised process to create targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9NPC2

UPID:

KCNK9_HUMAN

Alternative names:

Acid-sensitive potassium channel protein TASK-3; TWIK-related acid-sensitive K(+) channel 3; Two pore potassium channel KT3.2

Alternative UPACC:

Q9NPC2; Q2M290; Q540F2

Background:

Potassium channel subfamily K member 9, also known as TASK-3, is a pH-dependent, voltage-insensitive potassium channel. It plays a crucial role in maintaining the resting membrane potential and is involved in the physiological regulation of neuronal excitability. TASK-3 is alternatively named Acid-sensitive potassium channel protein TASK-3, TWIK-related acid-sensitive K(+) channel 3, and Two pore potassium channel KT3.2.

Therapeutic significance:

TASK-3's association with Birk-Barel syndrome, a condition marked by intellectual disability, hypotonia, hyperactivity, and facial dysmorphism, underscores its clinical importance. Understanding the role of TASK-3 could open doors to potential therapeutic strategies for managing this syndrome.